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Small-scale fisheries in Kenya contribute about 4.7% of the Gross Domestic Product (GDP) in spite of high post-harvest losses. Post-harvest interventions in fisheries enable fishers and fish processors to reduce waste, maintain nutritional aspects and meet stringent demands in food quality and safety. This review highlights the benefits and pitfalls of various fish post-harvest management interventions in order to drive policy dialogue and formulation of a regulatory framework for future interventions. It relies on data obtained from the Kenya Marine and Fisheries Research Institute and the State Department of Fisheries and Blue Economy. Results depict abundant interventions in both handling and processing, but low utilization (<40% of installed cold rooms, dryers and smoking kilns) and multiplication by fishing communities. Fish products that target export markets have wellorganized structures. However, a weak regulatory framework is a key constraint in addressing post-harvest management of fish intended for the domestic market. Under-utilization of installed interventions results in continued waste of fish, contributing to food and nutritional insecurity. This review recommends the development of an effective and integrative policy framework that involves interactions across different domains, institutional mechanisms that monitor and address those interactions, analytical bases for decision making, and multi-stakeholder dialogue for post-harvest management. Such policies will enhance the adoption of post-harvest technology in small-scale fisheries in Kenya and elsewhere.

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Lake Baringo (located in Kenya, East Africa) fishery is currently under perturbation with diverse annual fluctuations in the catch landings. In an attempt to remedy the declining fishery, Kenya Marine and Fisheries Research Institute, Fisheries Department and Beach Management Units, identified and demarcated three fish breeding areas for protection. To assess the effectiveness of these protected fish breeding areas, three fleets of multifilament gillnets (mesh sizes; 25.4 to 203.2 mm) were set between February and December 2018. One fleet was set inside the breeding area, whereas the other two fleets were set 200m and 400m outsides. Fish species abundance, size structure and maturity stages were analyzed from the catch. Fish species abundance was higher within fish breeding areas (67.8%) than outside (32.2%). Labeobarbus intermedius was the most abundant (55.3 %), followed by Oreochromis niloticus baringoensis (29.9%), Labeo cylindricus (13.2%) and Clarias gariepinus (1.7%). Even though larger fish sizes were recorded outside than inside fish breeding areas, they were not statistically different irrespective of seasons (P˃0.05). Majority of the fish (approx. 70%) both inside and outside the breeding areas were in gonad stages 1 and 2. The results indicate that the three areas have great potential to increase fish productivity through fish recruitment and subsequent spillover into fishing grounds. It is recommended that stakeholders, especially Beach Management Units and County Government Department of Fisheries, focus on actualizing the protection of fish breeding areas through enhanced monitoring and surveillance. Fishers should also be sensitized on protected areas concept, coupled with the need to use proper mesh sizes and fishing effort. Beach Management Units should be strengthened as co-management units to guarantee sustainable fisheries resource utilization in Lake Baringo.

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A major bottleneck to the application of machine learning tools to satellite data of African farms is the lack of high-quality ground truth data. Here we describe a high throughput method using youth in Kenya that results in a cost-effective method for high-quality data in near real-time. This data is presented to the global community, as a public good, on the day it is collected and is linked to other data sources that will inform our understanding of crop stress, particularly in the context of climate change.